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AbstractThe concentration of radiation-induced point defects in general materials under irradiation is commonly described by the point defect kinetics equations based on rate theory. However, the parametric uncertainty in describing the rate constants of competing physical processes, such as recombination and loss to sinks, can lead to a large uncertainty in predicting the time-evolving point defect concentrations. Here, based on perturbation theory, we derive up to the third-order correction to the solution of point defect kinetics equations. This new set of equations enables a full description of continuously changing rate constants and can accurately predict the solution up to 50% deviation in these rate constants. These analyses can also be applied to reveal the sensitivity of the solution to input parameters and aggregated uncertainty from multiple rate constants. [ABSTRACT FROM AUTHOR]

This paper describes a case study of continuous hydrologic modeling in the Brahmani River basin in India using the Hydrologic Engineering Center—Hydrologic Modeling System (HEC–HMS). The soil moisture algorithm (SMA) was employed as loss method for continuous simulations in the thirteen sub-basins. The sensitivity analysis showed that soil storage, tension storage and soil percolation are most sensitive parameters. The model performance was assessed for calibration period of 15 years (1990–2004) and validation period of 12 years (2005–2016), using statistical and visual evaluation techniques. During the calibration period, the observed and simulated values showed a good fit, with R2 ranging from 0.67 to 0.74, NSE from 0.66 to 0.72, and PBIAS from −8.5 to −9.5%. Similar performances are obtained during the validation period, with R2 ranging from 0.62 to 0.70, NSE from 0.60 to 0.68, and PBIAS from −2.5 to 21.4%. The results of the SMA procedure employed in the HEC-HMS model give valuable information for flood control and water supply management in the Brahmani Basin and similar other regions in Eastern India. [ABSTRACT FROM AUTHOR]

AbstractAn analysis of the stability margins of the innovative Holos-Quad microreactor design is presented. This high-temeprature gas-cooled reactor (HTGR) system is designed to operate fully autonomously with passive safety mechanisms. Therefore, the inherent stability of the reactor is of great importance. Using a point-reactor model, which couples point kinetics to thermal-hydraulic heat balance equations and includes reactivity feedback effects of the fuel and moderator temperatures, the closed-loop transfer function of the reactor is derived. Applying the approach of linear systems and control theory, both the gain and phase margins of the Holos-Quad design are obtained. The analysis demonstrates that the design is stable, with an infinite gain margin and a finite phase margin.A parametric uncertainty quantification study is also performed using a total Monte Carlo approach. The stability of the reactor for different power levels, such as during reactor startup or load-following transients, is also explored. Finally, two sensitivity analysis methods are applied, namely, multiple regression (deriving standardized regression coefficients) and variance-based sensitivity analysis (known as the Sobol method), to study the contribution of each of the parameters to the stability margins’ uncertainty. This analysis improves our understanding of the role of each of the parameters in the stability of the reactor. [ABSTRACT FROM AUTHOR]

Sample selection model is a solution to eliminate the nonresponse bias. In some applications nonresponse is a multilevel variable with respect to its reasons of occurring. In these cases, the sample selection model can be extended such that a model to be considered for each of the nonresponse reasons. Also, in many cases, the reasons for nonresponse have priority over each other. In other words, it is not possible to observe all of the nonresponse reasons simultaneously. For example, in a survey with two noncontact and refusal reasons, noncontact has priority over refusal and refusal can be observed if the contact to the respondent can be established. For analyzing such extended model, a Bayesian inference approach with multiple selection rules using multivariate normal, inverse gamma and LKJ distributions as prior distributions for parameters and possibility of priority for nonresponse reasons is presented. Simulation studies are performed and an establishment survey data set is analyzed to demonstrate the performance of the proposed method. For sensitivity analysis of nonresponse on the parameters of interest, posterior displacement is applied. [ABSTRACT FROM AUTHOR]

AbstractThis paper presents a new nonlinear epidemic model for the spread of SARS-CoV-2 that incorporates the effect of double dose vaccination. The model is analyzed using qualitative, stability, and sensitivity analysis techniques to investigate the impact of vaccination on the spread of the virus. We derive the basic reproduction number and perform stability analysis of the disease-free and endemic equilibrium points. The model is also subjected to sensitivity analysis to identify the most influential model parameters affecting the disease dynamics. The values of the parameters are estimated with the help of the least square curve fitting tools. Finally, the model is simulated numerically to assess the effectiveness of various control strategies, including vaccination and quarantine, in reducing the spread of the virus. Optimal control techniques are employed to determine the optimal allocation of resources for implementing control measures. Our results suggest that increasing the vaccination coverage, adherence to quarantine measures, and resource allocation are effective strategies for controlling the epidemic. The study provides valuable insights into the dynamics of the pandemic and offers guidance for policymakers in formulating effective control measures. [ABSTRACT FROM AUTHOR]

AbstractA statistical model finds application across various engineering and scientific contexts, aiding in the analysis and enhancement of heat transfer processes. Its utility extends to supporting scientists and engineers in gaining deeper insights into the impact of diverse factors on heat transfer and optimizing procedures for enhanced efficiency. Notably, the heat transfer efficiency of hybrid nanofluids containing ferromagnetic nanoparticles outperforms that of conventional fluids. In this study, a statistical model is utilized to predict the increased heat transfer rate in a heated shrinking sensor employing hybrid magnetic nanoparticles with slip restrictions. Incorporating radiative heat flux and heat source/sink components contributes novelty to the study. The model is converted into a non-dimensional form using appropriate similarity rules, and the resulting problem is solved computationally using bvp5c, a built-in function in MATLAB. Using advanced mathematical modeling and simulations, this research evaluates system performance in various scenarios and identifies optimal conditions for maximizing heat transfer rates. The study's main outcomes are; that including the thermal radiation and Prandtl number enhances the heat transfer rate, whereas the heat source decreases it. Further, the increased modified Hartmann number and suction parameter raise the shear rate coefficient. [ABSTRACT FROM AUTHOR]

AbstractIn connection to the various applications on energy conservation, fluid-based electronics; the coupling of electro-magnetic along with heat generation presents their significant approach. Therefore, the current investigation aims at analyzing the role of ferrite-water hybrid nanofluid in an Electro-Magnetohydrodynamics (EMHD) system. However, it utilizes the flow over a Riga plate with the variable properties of magnetization with the inclusion of thermal radiation and heat generation. Elucidating the influence of ferrite nanoparticles, the unsteady nature of the system addressed various properties of nanofluid. The system of equations is handled numerically adopting shooting-based fourth-order Runge-Kutta technique followed by similarity rules those are used to transformed the governing phenomena into ordinary. To maximize the EMHD efficiency, an optimization framework is employed using response surface methodology (RSM). However, to validate the work a hypothetical test is conducted with the help of analysis of variance (ANOVA). Through sensitive analysis, the key factors for the response of heat transfer rate are identified. Further, the measure outcomes of the results are; the inclusion of the ferrite nanoparticles with the increasing EMHD parameter the fluid velocity augments in magnitude. Further, increasing radiation the surface of the sheet became cool and it radiate from the surface region for which the fluid temperature boosts up. [ABSTRACT FROM AUTHOR]

Zika virus outbreak is creating a global public health hazard due to its increasing prevalence rate and neurological complication in affected individuals. In this work we have developed and studied an ODE compartmental Zika model with non-linear saturated incidence function and three control measures including prevention control from vector bite, treatment control of infected host and vector killing control. Our theoretical analysis shows that the disease free equilibrium is locally as well as globally asymptotically stable when the basic reproduction number is less than unity. The virus is uniformly persistent when the basic reproduction number is greater than unity. An endemic equilibrium point exists and locally stable when the basic reproduction number is greater than unity. The model is validated by fitting the model to real reported data of 2016 Zika outbreak in Puerto Rico and estimated the model parameters. We also have studied the basic reproduction number and effective reproduction number of the outbreak. Sensitivity analysis has been carried out to find most sensitive parameters. The optimal control and efficiency analysis has been done to find the policy of control variables. Lastly, the manuscript is ended by some conclusions. [ABSTRACT FROM AUTHOR]

This study estimates the effect of between-class ability grouping on Chilean secondary students' academic achievement. We rely on a structural feature of the school system: A considerable number of students who complete primary school must change schools to start their secondary education. Cardinality matching was performed to account for confounding variables. Sensitivity analysis was performed to address the fact that differences in unobserved variables could bias our findings. Results show that attending a school that groups students by ability causes a reduction in the average scores obtained in 10th grade of 0.07 SD for reading and 0.08 SD for mathematics. Students matched by their observed covariates could differ in their odds of attending a school with or without ability grouping by 15% for mathematics and 10% for reading, without altering our conclusions. Disadvantaged students are the most affected, whereas best-performing students do not benefit from this policy either. [ABSTRACT FROM AUTHOR]

Renewable energy technologies (RET) are expanding over the globe to fulfill the world's overall energy requirement. The main issue following the adoption of RET into power system network is an electrical islanding. It causes voltage, frequency, current, phase angle, power and harmonic content deviation outside the allowable limits, which may be hazardous to both connected apparatus and customers. It should be noticed within 2 s, according to Distributed Generation (DG) IEEE 1547 interconnection specifications. This research examines several islanding recognition strategies for improving the solidity of utility-connected DG. It will assist potential scholars in choosing the optimum islanding recognition technique with less non-detection zone (NDZ). The comparative assessment of various detection parameters analyzed in terms of NDZ, power quality issues and number of DG networks used. Finally, the sensitivity analysis of twenty passive methods carried out for low power mismatch cases like load switching and different fault cases, and the best methods for future islanding detection are recommended. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of equifinality in agent-based modeling (ABM) by introducing a novel sequential calibration approach. Equifinality arises when multiple models equally fit observed data, risking the selection of an inaccurate model. In the context of ABM, such a situation might arise due to limitations in data, such as aggregating observations into coarse spatial units. It can lead to situations where successfully calibrated model parameters may still result in reliability issues due to uncertainties in accurately calibrating the inner mechanisms. To tackle this, we propose a method that sequentially calibrates model parameters using diverse outcomes from multiple datasets. The method aims to identify optimal parameter combinations while mitigating computational intensity. We validate our approach through indoor pedestrian movement simulation, utilizing three distinct outcomes: (1) the count of grid cells crossed by individuals, (2) the number of people in each grid cell over time (fine grid) and (3) the number of people in each grid cell over time (coarse grid). As a result, the optimal calibrated parameter combinations were selected based on high test accuracy to avoid overfitting. This method addresses equifinality while reducing computational intensity of parameter calibration for spatially explicit models, as well as ABM in general. [ABSTRACT FROM AUTHOR]

Pounding between adjacent structures subjected to earthquake actions can cause significant damage. Due to the many uncertainties inherent to the seismic input and the impact phenomenon, a probabilistic assessment of the occurrence of seismic pounding and of its consequences on the structural performance is necessary. This work analyzes the problem of pounding by considering a single-degree-of-freedom benchmark system surrounded by rigid boundaries and subjected to a stochastic earthquake input. Although simplified, the model is representative of several realistic configurations, such as base-isolated systems surrounded by moat walls or bridge decks near the bridge abutments. The problem is cast in non-dimensional form and a parametric study is carried out to evaluate the influence of the identified non-dimensional input parameters on the statistics of the response. A probabilistic demand model is developed for the impact forces via non-linear regression, with the demand expressed as a function of the identified non-dimensional parameters. This model provides an estimate of median pounding force and of its dispersion given the seismic intensity of the input. Finally, global sensitivity analysis is used to rank the model parameters in terms of their influence on the system performance. [ABSTRACT FROM AUTHOR]

Reservoir operations involve determining the quantity of water to be released or stored from the reservoir at any given time, based on the reservoir's current condition. This research presents optimizing techniques for reservoir operating policies on Ravishankar Sagar reservoir during monsoon season. Metaheuristics algorithms – GA, NSGA II, NSGA III, and Eps MOEA were used to optimize the objective function for maximization of storage along with a different set of constraints in Ravishankarsagar reservoir. Sensitivity analysis on all algorithms was performed to calibrate different evaluation parameters. The results were analyzed to find the effectiveness of soft computing algorithms in real-world problems. The standard deviation of 359.52, 351.93,349.68 and 361.09 and Median of 512.5, 525.36,568.96 and 433.79 was observed in GA, NSGA II, Eps MOEA, and NSGA IIII so all the algorithms performed well and were in close approximation, with the least standard deviation and the most optimum storage in Eps MOEA. [ABSTRACT FROM AUTHOR]

In this article, a new modified deep learning (DL) method based on physics-informed neural networks (PINNs) is proposed for analyzing generalized coupled thermoelasticity in a porous material under shock loadings using Lord–Shulman (LS) theory. The PINN-based method demonstrates remarkable capabilities in solving differential equations and identifying unknown parameters. It is employed to solve a system of coupled partial differential equations (PDEs) governing a porous half-space material, considering thermal and strain relaxation coefficients in the LS theory. The optimal structure of the PINN is investigated through sensitivity analyses. Two adaptive sampling techniques, residual-based adaptive refinement (RAR) and residual-based adaptive distribution (RAD), are employed to enhance solution quality within the optimized architecture. The proposed forward PINN utilizes known values of field variables at initial and boundary conditions. The efficiency and effectiveness of the proposed PINN approach are demonstrated through three distinct scenarios. Non-parametric statistical tests and L2 relative error analysis validate the extraordinary potential of the proposed PINN-based method in accurately capturing the system behavior. The extrapolation results, represented as time history plots, showcase exceptional accuracy in this study, overcoming the limitations of conventional numerical methods in larger temporal domains. [ABSTRACT FROM AUTHOR]

This study aims to explore the performance of suppliers in the tourism and traveling sector. Therefore, we designed a case study in a cruise hotel and developed a team of experts to evaluate the existing suppliers. To rate suppliers, a grey multi-criteria decision-making (G-MCDM) platform is built to encounter the best-performing suppliers. CRITIC (CRiteria Importance Through Inter-criteria Correlation) and CoCoSo (combined compromise solution) methods are used. The results demonstrate that Food suppliers and Interior design maintenance services are selected as the best-performing actors in supply chain while suppliers for chemical cleaning materials are is rated as the worst. [ABSTRACT FROM AUTHOR]

AbstractShredder machines are essential for recycling plastic waste. They are used to shred plastic materials into smaller pieces, which can then be processed into new products. The shaft and rotary blades of the plastic shredder are its most crucial parts since they directly influence how effectively the machine shreds or recycles material. The shredder’s rotor is optimized based on the design of experiments and the response surface method. The natural frequencies and mode shapes are identified by modal analysis, and the critical natural frequencies that must be avoided during operation are identified through harmonic response analysis. The shredder’s rotor is optimized by determining its critical areas through a transient structural analysis. The optimization goals are attained by using the response surface method and experiment design in the ANSYS WORKBENCH DESIGN EXPLORATION module. The rotor of the optimized shredder is investigated, and its results are contrasted with the nominal design. The study of the optimum structure leads to a slight increase in mass of 2.43% in addition to reductions in equivalent stress and total deformation by about 9.84% and 42.86% respectively, as well as a 21.4%, 4.35%, and 4.48% increase in the first three natural frequencies, respectively. [ABSTRACT FROM AUTHOR]

AbstractTaillefer is a versatile Python tool for carrying out Sensitivity Analysis (SA) and uncertainty propagation (UP) studies based on Monte Carlo sampling. Developed with the primary goal of investigating sensitivities and uncertainties of steady-state thermal-hydraulic (SSTH) safety parameters of the high-performance research reactors Forschungs Neutronenquelle Heinz Maier-Leibnitz (FRM II) in Garching, Germany, and the Réacteur à Haut Flux (RHF) in Grenoble, France, it can also be used for a large variety of other modeling problems.The work presented here aims to explain the underlying mathematical background of SA and UP studies with Taillefer and to show some steps to verify these routines. Furthermore, a real-life application example is provided that demonstrates Taillefer’s use in SSTH analysis of the RHF. For this purpose, Taillefer is coupled to the external thermal-hydraulic software PLTEMP/ANL, which is one of the codes used at FRM II and RHF to access SSTH performance and safety parameters.Determining these crucial quantities is part of identifying possible low-enriched uranium (LEU) core designs that are suitable to replace the currently used highly enriched uranium fuels of the two reactors, supporting global nonproliferation efforts. Taillefer is a powerful tool in these conversion studies, as it increases the reliability of the LEU safety parameters by providing information about sensitivities and uncertainties in addition to the nominal values predicted by the thermal-hydraulic software. [ABSTRACT FROM AUTHOR]

AbstractA vibrating flip-flow screen (VFFS) is an effective solution for screening viscous and fine-grained materials. As one of the critical components, the load characteristics of the polyurethane screen panel primarily affect the fatigue life. However, more research is needed to understand the load characteristics of the screen panel. In this article, the discrete screen panel dynamic model is proposed to research the load characteristics of the screen panel based on the catenary model. The dynamic response parameters of the screen panel are obtained by the catenary model, and the finite element model of the screen panel is established to extract the dynamic characteristic parameters of the screen panel. The accuracy of the catenary model and the finite element model is verified by the experiment, and then the rationality of the dynamic theory is verified by the simulation. Moreover, the effects of hardness, amplitude, frequency, and angle on the tension and vibration strength of the screen panel are investigated. The results show that hardness, amplitude, frequency, and angle significantly affect the tension and vibration strength of the screen panel. The sensitivity of each factor on tension from high to low: amplitude > hardness > frequency > angle. Adjusting the value of each factor within a certain range is beneficial to increasing the vibration strength; meanwhile, it can reduce the tension of the screen panel. This research helps improve the service life and provides a theoretical basis for designing and optimizing the screen panel. [ABSTRACT FROM AUTHOR]

Crowd motion simulation requires specification of a range of parameters, each reflecting certain aspects of agent behavior. But what parameters matter the most? Are they all equally important? The question is important given that available data and resources for parameter calibration are limited, and priorities often need to be made. Here, for the first time, a full-spectrum sensitivity analysis of crowd model parameters is reported. It is shown that estimates of simulated evacuation time are, by far, most dependent on the value of locomotion/operational parameters, especially those that determine discharge rate at bottlenecks. The next most critical set of parameters are those that influence change of direction choices. If a crowd simulation model fails to reproduce bottleneck flows accurately, efforts to refine other modeling layers will be in vain. Similarly, if the model fails to represent exit choice adaptation/changing accurately, efforts to refine the exit choice model will be fruitless. [ABSTRACT FROM AUTHOR]

In smart buildings, dynamically controlled lighting and shading devices have a direct impact on occupants' thermal and visual comfort, building energy use, and peak demand. This study aims to assess the impacts of adjusting vertical and work plane illuminance sensor location and rotation for different zone orientations across different climate zones, on illuminance levels, glare, energy consumption, and demand. Using the sensor locations of 1.6 m and facing the window (typical assumption), when implementing the integrated shading and lighting controls, the lighting and cooling energy savings range from 41% to 71% across both heating and cooling-dominated climate zones. The greatest cooling peak use demand reduction of 6.5 kW (23%) is achieved in Climate Zone 2 A, where the total cooling and lighting demand savings are 28-33% (9-10 kW). The percent change in lighting energy use is greater as compared to the percent change in cooling energy use when sensor location is varied, however, the total kWh and kW change is greater for cooling in most climate zones. Results suggest that adjusting the sensor distance from the window has a greater impact on illuminance levels, glare, and lighting and cooling energy use in all climate zones as compared to sensor rotation. [ABSTRACT FROM AUTHOR]

Uranium is one of the most critical components in the nuclear field due to its chemical and radiological properties. Since few studies were conducted on uranium concentration in drinking water in Iranian cities, this study aimed to determine the concentration of uranium and flouridein the samples of drinking water collected from tap water in Shiraz, Fars province. Fifty samples were examined for uranium and fluoride presence using the ICP-MS and spectrophotometry methods. Hazard Quotient (HQ) and sensitivity analysis (SA) using the Monte Carlo Simulation technique with 10,000 iterations were applied to determine the human carcinogenic and non-carcinogenic effects of Uranium and Fluoride in three different groups (children, teenagers, and adults). The results showed that uranium and fluoride concentrations varied between 0.18–1.12 μg/L and 0.06–0.56 mg/L, respectively, which is less than the EPA recommendation for both elements. pH, EC, and TDS values were in accordance with the standard, and a positive correlation was observed between fluoride and total dissolved solids (TDS). The highest risk of carcinogenicity was found in the adult group with a value of 3.24E-9, lower than the allowable limit (1E-6). The highest hazard quotient (HQ) for uranium and fluoride was obtained in children with 0.13 and 0.66. Monte Carlo simulation results showed that the hazard quotient (HQ) for both elements in all groups was less than one and consistent with the values of the deterministic method. Also, water swallowing rate and contaminant concentration were the most influential parameters in the sensitivity analysis. [ABSTRACT FROM AUTHOR]

Non-destructive evaluation of the spatially resolved residual stresses from limited measurement data is crucial for a comprehensive assessment of structural integrity and performance reliability of engineering components. Generally, residual stresses are caused by incompatible internal eigenstrains and along this line, a novel sensitivity-based eigenstrain reconstruction approach is developed in this work for residual stress identification in thin plates using vibrational modal data. There are two key ingredients in establishing the proposed approach. At first, residual stresses are parameterised through direct eigenstrain analysis and thereafter, residual stress reconstruction is recast as a parameter identification problem whose goal function is just the least-squares of the misfit between the measured and calculated data. Second, to minimise the nonlinear least-squares goal function, the modal sensitivity analysis is called to linearise the misfit and the trust-region constraint is invoked in conjunction with the Tikhonov regularisation to enhance the convergence. Numerical examples are investigated to verify the robustness, accuracy and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Shimmy is one of the important factors affecting the ride comfort and lateral stability of straddle-type monorail vehicles with single-axle bogies (SMVS). To obtain the main parameters affecting SMVS shimmy, a global sensitivity analysis strategy for SMVS shimmy is proposed. The shimmy response surface model is constructed, and the sensitivity analysis of the shimmy response surface model is carried out by the Sobol method. Based on this, the shimmy factor model of SMVS is established by factor analysis method. A novel SMVS shimmy analysis method based on factor model is proposed. The shimmy factor model is verified by the dynamic model of SMVS. The results show that 11 main factors affecting the shimmy are obtained by sensitivity analysis. Through the dimension reduction technology of factor analysis, four main factors affecting SMVS shimmy are extracted. The complex coupling relationship between the shimmy factors of SMVS is revealed. The established shimmy factor model can effectively analyse the shimmy state of SMVS, and the dynamic simulation results also show consistency. This study not only proposes a new perspective to understand the SMVS shimmy mechanism, but also provides the foundation for further optimal design of monorail vehicle stability. [ABSTRACT FROM AUTHOR]

The virtual synchronous machine (VSM) concept is emerging as a flexible approach for controlling power electronic converters in grid-connected and standalone applications. In this study, we have used the mathematical model of a Virtual machine with a virtual exciter and governor for the standalone inverter to optimize the parameter for small-signal stability. Firstly, the small-signal models of virtual synchronous generator with load have developed, and subsequently, the system eigenvalues were obtained by solving the state Jacobian matrix. Next, the sensitivity of the eigenvalue location on controller parameters has been studied. The parameters are optimized on the basis of the location of dominant eigenvalues using a genetic algorithm. Finally, the optimal controller parameters are used to test the system's dynamics by solving the model equations with Ordinary Differential Equation (ODE) solver. Moreover, our conclusions were also tested using the actual switching devices on Matlab/Simulink. The results indicate that the frequency stability can be enhanced drastically by optimizing a wide range of VSM parameters. The frequency stability sensitivity with respect to load variation has been improved. The transient settling time of system response for optimized values is 0.25 sec which is only 5% of that for general values. The results of this work are relevant for the VSM-based microgrid small-signal stability analysis. [ABSTRACT FROM AUTHOR]

Velocity string (VS) is one of the most common methods to unload water in gas-producing field. In order to understand the behavior affecting production rate, we obtained several parameters including well completion, gas well production data, gas liquid ratio (GLR) and pressure data at tubing and casing head pressure, flowing bottom hole pressure. We then explore the relationship between these parameters against reservoir pressure and perform sensitivity analysis using multiphase steady-state flow simulator to analyze the parameters are the most sensitive to gas production rate. The results show that: (1) at larger inner diameter of the VS, there is a certain increase trend of gas production of gas wells. However, the production rate does not show a linear increase relationship with the larger internal diameter. It will reach certain inflection point before it decreases; (2) the gas production of the VS well is mainly driven by the reservoir pressure, the higher the reservoir pressure, the greater the gas production; (3) the root cause of relatively low initial production rate after small inner diameter coiled tubing VS installation is categorized as an abnormal well startup. This study provides theoretical support for selecting the optimum size and depth of VS to maintain well productivity. [ABSTRACT FROM AUTHOR]

Modern supply chain operates in a highly uncertain environment caused by natural disasters and market changes. Such a fact has motivated academics and practitioners to pay more attention to the supply chain resilience. This paper reports on designing a resilient supply chain under uncertain environment by an uncertain programming method. The desired resilience level against disruption is achieved with less redundancy by controlling them in the presented models. And parameter uncertainty caused by the limited historical data is also addressed using uncertainty theory. To cope with the problem's complexity, we convert the proposed models into their deterministic formulations, which can easily be solved by cplex solver. The results from sensitivity analysis demonstrate the necessity of including uncertainty during the planning phase of supply chain network design. The performance of resilience constraint and the positive effect of sticker redundancy constraint in improving service level are also investigated fully. [ABSTRACT FROM AUTHOR]

Velocity string (VS) is one of the most common methods to unload water in gas-producing field. In order to understand the behavior affecting production rate, we obtained several parameters including well completion, gas well production data, gas liquid ratio (GLR) and pressure data at tubing and casing head pressure, flowing bottom hole pressure. We then explore the relationship between these parameters against reservoir pressure and perform sensitivity analysis using multiphase steady-state flow simulator to analyze the parameters are the most sensitive to gas production rate. The results show that: (1) at larger inner diameter of the VS, there is a certain increase trend of gas production of gas wells. However, the production rate does not show a linear increase relationship with the larger internal diameter. It will reach certain inflection point before it decreases; (2) the gas production of the VS well is mainly driven by the reservoir pressure, the higher the reservoir pressure, the greater the gas production; (3) the root cause of relatively low initial production rate after small inner diameter coiled tubing VS installation is categorized as an abnormal well startup. This study provides theoretical support for selecting the optimum size and depth of VS to maintain well productivity. [ABSTRACT FROM AUTHOR]

Due to importance of cell voltage and caustic current efficiency (CCE) in chlor-alkali industry, the necessity of accurate approach for prediction these parameters has become evident. In the current work, an extreme learning machine (ELM) approach is used to this end. Determination of the statistical qualities including R2 and different types of error reveals the fact that ELM method is suitable tool for calculation of CCE and cell voltage. The determined R2 values for CCE and cell voltage are equal to 1. Furthermore, RMSE values are 0.00002 and 1.3 × 10−6 for cell voltage and CCE, respectively. On the other hand, different graphical methods confirmed this acclaim. Moreover a sensitivity analysis is used to show effect of brine concentration, current density, operating temperature, electrolyte velocity, run time and pH on cell voltage and CCE. This analysis concluded to the fact that brine concentration and current density have the most effects on CCE and Cell voltage, respectively. [ABSTRACT FROM AUTHOR]

The study examines the magnetohydrodynamic flow of engineered fluid past an extending cylinder, analyzing the effects of non-linear radiation and an inclined magnetic field. The physical problem generates a system of non-linear coupled partial differential equations, and the system is transformed into ordinary differential equations using similarity transformation and solved using the Runge-Kutta method and shooting technique. Also, sensitivity analysis is taken into account to observe the input variables effects on skin friction and heat transfer rate. The study reveals that magnetic field orientation, nonlinear radiation effects, and injecting more core fluid significantly impact heat transfer characteristics. The effects of angle of orientation, magnetic field, suction parameter, and volume concentration on skin friction are significant. Reynolds number significantly affects heat transfer rate by 62.15% for suction. The findings can be applied in physics and engineering to control heat transfer between stretching surfaces and engineered fluids. [ABSTRACT FROM AUTHOR]

AbstractSimulation of a station blackout (SBO) scenario was carried out for an open pool–type nuclear research reactor. The SBO transient was analyzed using the best estimate (BE) thermal-hydraulic code RELAP5/MOD3.2 to evaluate the performance of safety systems and inherent thermal inertia provided by the reactor pool in ensuring adequate core cooling during a prolonged SBO condition lasting up to 7 days. This encompasses assessment of cooling provided by battery-operated auxiliary pumps in the initial phase followed by setup of the natural convection cooling mode for the extended period. Best Estimate Plus Uncertainty (BEPU) methodology was applied for assessment of safety margins. This involved estimation of required simulations using the Wilks first-order formulation to achieve results within the tolerance limit of 95/95. Identification of relevant uncertainties and their propagation was carried out; subsequently, a case matrix for 59 simulation runs was generated using the Latin hypercube sampling method. The upper/lower bounds of uncertainty results were analyzed and compared with the BE code results. Later, sensitivity analysis was carried out using sensitivity coefficients generated using the Pearson and Spearman coefficient. The results show that the values of the crucial thermal-hydraulic parameters obtained with the tolerance limit of 95/95 met the acceptance criteria, with adequate safety margins. [ABSTRACT FROM AUTHOR]

The emphasis of this study is the numerical analysis via D2Q9-based Lattice Boltzmann Method of free convection MHD non-Darcy flow in hybrid nanofluid (TiO2/Cu–water) occupying a differentially heated square enclosure. A key novelty of the work is the inclusion of a response surface methodology (RSM)-based sensitivity analysis. The current investigation has been done considering the variation in Rayleigh number (103 ≤ Ra ≤ 106), Darcy number (0.0001 ≤ Da ≤ 0.1), and Hartmann number (0 ≤ Ha ≤ 50). From RSM, high Darcy parameter, low volumetric fraction, and low Hartmann number are identified as the optimum functioning conditions for heat transfer rates. [ABSTRACT FROM AUTHOR]

AbstractAs the oilfield fully enters the late stage of exploitation, the water content in the oil and gas transportation pipelines is rising. Meanwhile, the high-pressure and low-temperature environment inside the pipeline facilitate the formation of hydrates, which will seriously block the mixing pipeline and cause a series of production safety problems. Therefore, it is necessary to control the risk under the high water content system. In this paper, a high-pressure flow loop device with a viewable window was used to study the formation characteristics of carbon dioxide hydrate in a pure water system, and the effects of the liquid loading, pressure, volume flow rate, and two inhibitors, polyvinylpyrrolidone (PVP) and propylene glycol methyl ether (PM), on the induction time of carbon dioxide hydrate formation were investigated. The experimental results showed that the amount of liquid loading, pressure, volume flow rate, and inhibitor had a significant effect on the hydrate induction time. In addition, the ether compounds PM and PVP have inhibitory synergistic effects, which can significantly prolong the hydrate induction time, and the inhibitory synergistic effect is further enhanced with the increase of PM concentration, which further suggests the synergistic inhibition mechanism of the two. Based on the standard regression coefficient method, the factors affecting the induction time were subjected to sensitivity analysis, and it was found that the inhibitor was the most important factor affecting the induction time. Therefore, future research should also focus on finding better performance of inhibitors, synergists and their ratio. [ABSTRACT FROM AUTHOR]

AbstractIn this article, I propose a tractable approach to Bayesian inference in a simple linear regression model for which the standard exogeneity assumption does not hold. By specifying a beta prior for the squared correlation between an error term and regressor, I demonstrate that the implied prior for a bias parameter is t-distributed. If the posterior distribution for the identified regression coefficient is normal, this implies that the posterior distribution for the unidentified treatment effect is the convolution of a normal distribution and a t-distribution. This result is closely related to the literatures on unidentified regression models, imperfect instrumental variables, and sensitivity analysis. [ABSTRACT FROM AUTHOR]

Dynamic crop models are powerful tools for evaluating crop responses to alternative management options. These models consist of various input parameters that need calibration before being implemented in a new environment. Sensitivity analysis (SA) has proven to be an efficient method for identifying dominant model parameters. This study aimed to determine influential parameters of the AquaCrop model for basil and also quantify output uncertainty under different nitrogen fertilizer rates. The Sobol' SA method was employed to compute both first-order and total-order sensitivity indices. Results indicated that normalized water productivity (WP*) and crop coefficient (KcTr,x) were the most influential parameters across all treatments. Furthermore, as fertility stress increased, the interaction effects among parameters decreased. The temporal analysis of model output (biomass) revealed that parameter sensitivities were highly time-dependent. In addition, the uncertainty of predicted biomass was determined using combined violin and box plots. Results demonstrated that the optimal nitrogen fertilizer application rate extended the distribution of model output. In summary, these findings offer valuable insights for model simplification and effective decision-making. [ABSTRACT FROM AUTHOR]

Estimating an individual treatment effect (ITE) is essential to personalized decision making. However, existing methods for estimating the ITE often rely on unconfoundedness, an assumption that is fundamentally untestable with observed data. To assess the robustness of individual-level causal conclusion with unconfoundedness, this article proposes a method for sensitivity analysis of the ITE, a way to estimate a range of the ITE under unobserved confounding. The method we develop quantifies unmeasured confounding through a marginal sensitivity model, and adapts the framework of conformal inference to estimate an ITE interval at a given confounding strength. In particular, we formulate this sensitivity analysis as a conformal inference problem under distribution shift, and we extend existing methods of covariate-shifted conformal inference to this more general setting. The resulting predictive interval has guaranteed nominal coverage of the ITE and provides this coverage with distribution-free and nonasymptotic guarantees. We evaluate the method on synthetic data and illustrate its application in an observational study. for this article are available online. [ABSTRACT FROM AUTHOR]

In the condition of actual obstacle avoidance, where longitudinal deceleration is large and variable, it is difficult for the autonomous vehicle to simultaneously track longitudinal velocity and lateral motion. In addition, when the planned trajectory exceeds the adhesion of the road, the vehicle is also prone to losing stability. Most studies of the obstacle avoidance process only consider constant velocity. This paper presents a novel control architecture for four-wheel driving (4WD) and four-wheel steering (4WS) autonomous vehicles to track predefined trajectory and velocity. It is proposed to use preview technology to obtain the desired state of the vehicle and a controller based on multi-input multi-output nonlinear model predictive control (MIMO-NMPC) that considers the deceleration-steering combination condition. According to the sensitivity analysis of the influence of tyre slip rate on tyre lateral force, the optimal working boundary of the tyre is determined. The output of the controller is constrained by estimating tyre force to prevent tyre force saturation and maximise tyre adhesion limit utilisation. The simulation results demonstrate that the proposed controller can better track the trajectory and longitudinal velocity with a faster response on the high-adhesion road. The overshoot of lateral displacement and the maximum error of longitudinal velocity are less than 0.03m and 0.2m/s, respectively. In addition, when the planned trajectory exceeds the adhesion limit of the road, it can still follow the desired trajectory as closely as possible while maintaining stability on low-adhesion roads. [ABSTRACT FROM AUTHOR]

In the framework of risk assessment in nuclear accidents, simulation tools are widely used to understand and model physical phenomena. These simulation tools take into account a large number of uncertain input parameters. We often use Monte Carlo–type methods to explore their range of variation: The input space is randomly sampled, and a code run is performed on each sampled point. However, some of these code runs may fail to converge. Analyzing these code failures to understand which of the inputs have the most influence on them leads to a better understanding of how the code works. It also intends to improve the robustness of the simulation software and code computations. For this purpose, we propose two complementary approaches performing a statistical analysis of the code failures. The first approach is based on goodness-of-fit tests and compares conditional probability distributions according to code failures to a reference one. A second approach, based on a dependence measure named the Hilbert-Schmidt Independence Criterion, provides another way to measure the global dependence between the inputs and the code failures. The development of this methodology is carried out in the context of severe nuclear accidents. More especially, the presented methods are applied for the study of the simulation code MC3D, which simulates the fuel-coolant interaction in a severe nuclear accident context. [ABSTRACT FROM AUTHOR]

AbstractIntroducing pulsatility in LVADs is known to reduce complications such as stagnation and thrombosis, but it is an ongoing topic of research on what the optimal form is. We present a framework consisting of parametrized full-order simulations, reduced-order models, and sensitivity analysis to systematically quantify the effects of parametrized pulsatility on washout. As a sample problem, we study the washout in an idealized 2D left ventricle and a parametrized sinusoidal LVAD flow rate. The framework yields speed-ups proportional to the number of samples required in the sensitivity analysis. In our setting, we find that short, intense pulses wash out the left ventricle best, while the time between consecutive pulses does not play a significant role. [ABSTRACT FROM AUTHOR]

This article aims to simulate natural gas vehicle (NGVs) refueling station located in Bucharest, which includes an on-board cylinder, reservoir tanks, connecting pipes, and a reciprocating compressor using thermodynamic analysis. Tanks' pressures during the filling process were changed: 180-200, 200-220, and 220-235 bar for low, average and high pressure respectively. Furthermore, sensitivity analyses were implemented to study changing the cylinder initial pressure and the influence of vehicles' number alteration. The simulation result for mass flow rate is close to the experimental measurements. Additionally, the higher the initial pressure inside vehicle tank, the lower mass delivered and the shorter loading time. Finally, this study helps the government to increase the environmentally friendly fuel in the local market. [ABSTRACT FROM AUTHOR]

The use of simulation-based sensitivity analyses is fundamental for evaluating and comparing candidate designs of future clinical trials. In this context, sensitivity analyses are especially useful to assess the dependence of important design operating characteristics with respect to various unknown parameters. Typical examples of operating characteristics include the likelihood of detecting treatment effects and the average study duration, which depend on parameters that are unknown until after the onset of the clinical study, such as the distributions of the primary outcomes and patient profiles. Two crucial components of sensitivity analyses are (i) the choice of a set of plausible simulation scenarios and (ii) the list of operating characteristics of interest. We propose a new approach for choosing the set of scenarios to be included in a sensitivity analysis. We maximize a utility criterion that formalizes whether a specific set of sensitivity scenarios is adequate to summarize how the operating characteristics of the trial design vary across plausible values of the unknown parameters. Then, we use optimization techniques to select the best set of simulation scenarios (according to the criteria specified by the investigator) to exemplify the operating characteristics of the trial design. We illustrate our proposal in three trial designs. for this article are available online. [ABSTRACT FROM AUTHOR]

The eigenvalues and eigenvectors of the Fisher Information Matrix (FIM) can reveal the most and least sensitive directions of a system and it has wide application across science and engineering. We present a symplectic variant of the eigenvalue decomposition for the FIM and extract the sensitivity information with respect to two-parameter conjugate pairs. The symplectic approach decomposes the FIM onto an even-dimensional symplectic basis. This symplectic structure can reveal additional sensitivity information between two-parameter pairs, otherwise concealed in the orthogonal basis from the standard eigenvalue decomposition. The proposed sensitivity approach can be applied to naturally paired two-parameter distribution parameters, or a decision-oriented pairing via regrouping or re-parameterization of the FIM. It can be used in tandem with the standard eigenvalue decomposition and offer additional insights into the sensitivity analysis at negligible extra cost. for this article are available online. [ABSTRACT FROM AUTHOR]

Most of the reported optimizations of micro-channel evaporators focus on specific variables, their priority has not been revealed. In the present study, a numerical model for a louvered micro-channel evaporator is established. The operating patterns under different cases are first revealed. Then, sensitivity analysis of operational and structural parameters is analyzed; sensitivity coefficients are additionally revealed to enumerate the priority. The results indicate that the influence mechanism and sensibility of different operating factors are distinct. The log-mean temperature difference (LMTD) increases first and then decreases with the air speed while the overall heat transfer coefficient increases first and then decreases with the inlet dryness. In other cases, the LMTD, heat transfer rate, entropy generation, and overall heat transfer coefficient display positive or negative variation trends with the operating factors. On the whole, the air speed, initial air temperature, and mass flow rate of the refrigerant play positive roles while the cross-sectional size and inlet dryness play opposite roles in determining the heat transfer performance. Of which, the heat transfer rate is positively determined by the initial air temperature with the maximum value of 0.85 while negatively determined by the inlet dryness with the value of −0.23; the overall heat transfer coefficient is positively determined by the air speed with the value of 0.83 while negatively determined by the cross-sectional size with the maximum value of −0.41. The mass flow rate of the refrigerant makes no difference in determining the heat transfer performance. [ABSTRACT FROM AUTHOR]

This work focuses on the effect of wrinkle defects within curved laminate composites under compressive load. In the study, 22 curved specimens with different levels of maximum misalignment angles – ranging from 1.5° to 17° – were manufactured. The specimens with embedded defects were tested under compression to assess the effect of defects on the compressive strength. Then, specimens were modeled using the Discrete Ply Model strategy and simulations were run. The numerical model showed a relevant correlation with the experimental results and was used to distinguish the influence of different failure mechanisms (matrix cracking, delamination and fiber failure) on the global failure of the specimen. Finally, a numerical sensitivity analysis of the compressive strength of curved specimens in relation with the misalignment angle was carried out. [ABSTRACT FROM AUTHOR]

Sensitivity analysis methods have found extensive use in nuclear criticality safety applications for understanding the impact of uncertain nuclear data on eigenvalue estimates. Significant uncertainty exists in nuclear data and nuclear physics models for photon and electron transport applications, and the goal of this work is to explore whether recently developed adjoint-based, first-order generalized perturbation theory reaction rate sensitivity methods can be extended to coupled Monte Carlo radiation transport simulations. This paper presents a rigorous theoretical derivation for this extended sensitivity analysis method, which is then implemented in a one-dimensional test Monte Carlo code. The adjoint-based sensitivity coefficients are found to agree well with reference direct perturbation and deterministic SENSMG sensitivity coefficients for a simple test problem. [ABSTRACT FROM AUTHOR]

In order to study the influence of the space linkage system on the stability of the straddle-type monorail vehicle with single-axle bogies, the sensitivity analysis of the space linkage system is identified based on the Pearson coefficient method to determine the importance of each component of the single-axle bogies. The dynamics model of straddle-type monorail vehicle with single-axle bogies is established by the multi-rigid body dynamics. The Pearson analysis method is used to identify the key parameters of the space linkage system. Based on that, dynamic response optimization model of space bar system is developed to carry out a multi-objective suspension design optimization process. The results show that the maximum sensitivity parameter for the RMS value of yaw acceleration and pitch angle acceleration is the length of the longitudinal tow bar; there is a correlation of approximately 0.088 between the stiffness K and the damping coefficient C of the hydraulic shock absorber. After optimization the root mean square of lateral acceleration of the optimized single-axle bogie vehicle is reduced by 6.0%. [ABSTRACT FROM AUTHOR]

Our aim is to explore novel optical solitons within the context of an extended higher-order nonlinear Schrödinger equation that governs the behaviour of propagating light waves. Primarily, this research finds abundant types of solitons, such as singular, kink and trigonometric functions subject to certain constraint conditions. We have utilized G /(bG + G + a)- expansion method, which has proved effective in retrieving these solitons and presenting them for further analysis. The model’s dynamic behaviour is then investigated through bifurcation, quasi-periodic oscillations, chaotic behaviour, and sensitivity. These include methods like phase portrait rendering, time series scrutiny, Lyapunov exponents calculation, and the assessment of multi-stability. Finally, sensitivity analysis is conducted at three distinct initial conditions, revealing that the model displays a high level of sensitivity, with substantial alterations occurring in response to minor changes in the initial conditions. The results of this study are revolutionary, intriguing, and possess crucial theoretical importance in evolution disruptions. [ABSTRACT FROM AUTHOR]

The high thermal efficiency of supercritical water makes it a promising alternative to water cooled reactors. This study employs numerical analysis, utilizing the SST k-ω turbulence model, to investigate the heat transfer performance of supercritical water (SCW) in various tube configurations and fluid flow conditions across Reynolds numbers ranging from 8,000 to 20,000. This research examines how different geometrical parameters, such as the helical direction, number of lobes, and cross-sectional shape, impact the flow physics and heat transfer performance of different spiral tubes. The outcomes specify that increasing the lobed number in the tube improves the heat flux by about 5%–16%. Furthermore, introducing two direction changes in the twisted tube will cause a slight increase (about 20%) on heat transfer enhancement. Finally, the sensitivity analysis of heat flux and Nusselt number to each of the effective parameters in the heat transfer of supercritical water in twisted tubes has been accomplished and the Response Surface Method (RSM) utilizes the central composite design (face-centered) approach. According to the findings of these two studies, it has been established that the Reynolds number of the fluid flow is the most influential parameter in determining the extent of heat transfer. Specifically, it exerts an effectiveness of 26% and 76% on the Nusselt number and heat flux, respectively. Furthermore, the inscribed circle diameter of tube by 8% effectivity and minor axis length by 5% effectivity on heat flux are more effective than others. [ABSTRACT FROM AUTHOR]

Carbon-dioxide (CO2) centrifugal compressors are machines with high potential of usage in power generation plants and oil industry as it achieves high thermal efficiency in the Brayton cycles and contributes to oil production through the capture and storage of CO2 (CCS) in EOR (Enhanced Oil Recovery) systems. High levels of static pressure at the outlet are desired for EOR applications, which are usually obtained through the insertion of vanes in the diffuser. This work intends to increase vaneless-diffuser static pressure recovery by modifying only its meridional profile, ensuring a broader range of off-design operation when compared to vaned diffusers and attending to the fluctuations of mass flow and rotation expected in EOR practical applications. Therefore, a parametric optimization through surrogate model coupled to CFD was performed with three different objective functions that were submitted to single-optimization through the NSGA-II method: Maximize total-to-total polytropic efficiency, minimize total pressure loss coefficient or maximize static pressure recovery coefficient. Additionally, a sensitivity analysis was conducted using Morris Elementary Effects and SS-ANOVA. The results indicated that the optimized geometries increased the total-to-total polytropic efficiency by 2.9%, reduced the total pressure loss coefficient by 24.0% and increased the static pressure recovery coefficient at the design point by 11.4%, which is discussed in detail after a careful phenomenology assessment. The strategy adopted in the present work through a combination of Sensitivity Analysis, surrogate models and CFD increased the vaneless-diffuser static pressure recovery without the need of inserting vanes in the diffuser, which avoid instabilities in the equipment and would restrict its range of off-design operation. [ABSTRACT FROM AUTHOR]

Solar irradiance and temperature are two primary factors that affect the energy generation efficiency of solar photovoltaic (PV) systems, meaning that climate change may significantly impact the production of solar energy in the future. In this study, a two-way sensitivity analysis is carried out to determine the energy generation potential under future climate change conditions, and conditions of shadow covering are also considered. The simulation results indicate that the impact of solar irradiance causes the most variation in energy generation, and that shadow covering has a weak impact on the output. In the one-way sensitivity analysis, solar irradiance makes a ± 18% difference in energy generation, whereas shadow covering represents about ± 2%. In the future trend of climate change in the world and Taiwan, the energy generation potential can decrease up to 21% and increase 8%, respectively, mainly corresponded by solar irradiance. We suggest that compared with the issue of temperature, the efficiency of solar irradiance usage is more important, especially in view of the global trend toward solar irradiance loss. Taiwan also suffers the issue, but the different trend of climate change impact may make the challenge different. [ABSTRACT FROM AUTHOR]

The heat extraction process of the Enhanced Geothermal System (EGS) faces the problem of mechanical property degradation caused by artificial cracks and surrounding rock caused by water-cooling shock. However, there are few studies considering the effect of water-cooling shock on fracture deformation and heat production performance. Therefore, a comprehensive numerical model considering water-cooling shock was established to simulate the heat extraction process of EGS. Four different scenarios were designed to analyze the influence of water-cooling shock on the heat production performance of EGS. The sensitivity analysis of several important variables affecting fracture aperture and heat production performance is carried out. The results show that compared with EGS without considering water-cooling shock, the heat extraction performance of EGS considering water-cooling shock is more reasonable. For a reservoir with an initial temperature of 300°C, the decrease of production temperature after 40 years is 3.35°C. Water-cooling shock changes the fracture aperture by degrading the elastic modulus of rocks and fractures, which affects the heat production performance of EGS. The decrease of fracture elastic modulus means that the fracture aperture increases under the same injection water pressure and confining pressure. The decrease of elastic modulus of bedrock leads to the decrease of stress sensitivity index, which inhibits the expansion of fracture aperture. Comprehensively considering water-cooling shock on reservoirs and fractures will more reasonably predict the heat production performance of EGS. [ABSTRACT FROM AUTHOR]